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Classification of Characters in Movie by Correlation Analysis of Genre and Linguistic Style

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2019, 24(1), pp.49-55
  • DOI : 10.9708/jksci.2019.24.01.049
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : November 29, 2018
  • Accepted : December 13, 2018
  • Published : January 31, 2019

YOU Eun-Soon 1 Jaewon Song 2 Seung Bo Park 1

1인하대학교
2(주)밸류파인더스

Accredited

ABSTRACT

The character dialogue created by AI is unnatural when compared with human-made dialogue, and it can not reveal the character’s personality properly in spite of remarkable development of AI. The purpose of this paper is to classify characters through the linguistic style and to investigate the relation of the specific linguistic style with the personality. We analyzed the dialogues of 92 characters selected from total 60 movies categorized four movie genres, such as romantic comedy, action, comedy and horror/thriller, using Linguistic Inquiry and Word Count (LIWC), a text analysis software. As a result, we confirmed that there is a unique language style according to genre. Especially, we could find that the emotional tone than analytical thinking are two important features to classify. They were analyzed as very important features for classification as the precision and recall is over 78% for romantic comedy and action. However, the precision and recall were 66% and 50% for comedy and horror/thriller. Their impact on classification was less than romantic comedy and action genre. The characters of romantic comedy deal with the affection between men and women using a very high value of emotional tone than analytical thinking. The characters of action genre who need rational judgment to perform mission have much greater analytical thinking than emotional tone. Additionally, in the case of comedy and horror/thriller, we analyzed that they have many kinds of characters and that characters often change their personalities in the story.

Citation status

* References for papers published after 2022 are currently being built.

This paper was written with support from the National Research Foundation of Korea.